ABSTRACT
Understanding value learning in animals is a key focus in cognitive neuroscience. Current models used in research are often simple, and while more complex models have been proposed, it remains unclear which assumptions align with actual value-learning strategies of animals. This study investigated the computational mechanisms behind value learning in pigeons using a free-choice task. Three models were constructed based on different assumptions about the role of the basal ganglia's dual pathways and synaptic plasticity in value computation, followed by model comparison and neural correlation analysis. Among the three models tested, the dual-pathway reinforcement learning model with Hebbian rules most closely matched the pigeons' behavior. Furthermore, the striatal gamma band connectivity showed the highest correlation with the values estimated by this model. Additionally, enhanced beta band connectivity in the nidopallium caudolaterale supported value learning. This study provides valuable insights into reinforcement learning mechanisms in non-human animals.
Footnotes
Author contributions
Conceptualization: F.J., Lifang Yang, Z.S.; Data curation: F.J., Long Yang; Formal analysis: F.J.; Funding acquisition: M.L.; Investigation: F.J.; Methodology: F.J.; Project administration: Lifang Yang; Resources: Z.S.; Software: F.J., Long Yang; Supervision: Lifang Yang, Z.S.; Validation: F.J., Lifang Yang; Visualization: Long Yang; Writing – original draft: F.J.; Writing – review & editing: M.L., Lifang Yang, Z.S.
Funding
This work was funded by National Natural Science Foundation of China grant 62301496, National Postdoctoral Researcher Program grant GZC20232447 and Key Scientific and Technological Projects of Henan Province grants 252102210008 and 252102311095.
Data and resource availability
The datasets analyzed in the current study are available from the corresponding author on reasonable request.
